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Network Intrusion Detection System Using Random Forest and Decision Tree Machine Learning Techniques

  • T. Tulasi BhavaniEmail author
  • M. Kameswara Rao
  • A. Manohar Reddy
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1045)

Abstract

In the network communications, network interruption is the most vital concern these days. The expanding event of the system assaults is a staggering issue for system administrations. Different research works are now directed to locate a successful and productive answer for forestall interruption in the system so as to guarantee to arrange security and protection. Machine learning is a successful investigation device to identify any irregular occasions happened in the system traffic stream. In this paper, a mix of the decision tree and random forest algorithms is proposed to order any strange conduct in the system traffic.

Keywords

Machine learning Random forest Decision tree 

References

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    Garcia-Teodoroa, P., Diaz-Verdejoa, J., Macia- Fernandeza, G., Vazquezb, E.: Anomaly-Based Network Intrusion Detection: Techniques, Systems and Challenges. Department of Telematic Engineering, Universidad Politécnica de Madrid, Madrid, Spain (2009)Google Scholar
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    Zamani, M., Movahedi, M.: Machine Learning Techniques for Intrusion Detection. Cornell University, 2 (2015)Google Scholar
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    Tiwari, M., Kumar, R., Bharti, A., Kisan, J.: Intrusion detection system. Int. J. Tech. Res. Appl. 5, 38–44 (2017)CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • T. Tulasi Bhavani
    • 1
    Email author
  • M. Kameswara Rao
    • 1
  • A. Manohar Reddy
    • 1
  1. 1.KL Deemed to be UniversityGuntur DistIndia

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